As the inversion matrix of Eq. (REF ) has size \(N \times N\) , in order to achieve high efficiency, we use a gradient descent method to optimize the functional iteratively, in which the step size controls how far the iterate moves along the gradient direction during the current iteration. Instead of setting the step size manually, we use a backtracking line search to enforce convergence [1]}.
